Imagine being able to chat with your documents, generate captivating content from them, and access the power of Azure OpenAI models on your data. This is what Document Generative AI, a breakthrough solution from Azure AI Document Intelligence (former aka Azure Form Recognizer) and Azure OpenAI Service, can do for you.
In the context of enterprise applications, the question we hear most often is “how do I build something like ChatGPT that can read my documents and uses my documents as the basis for its responses?”
Document Generative AI, powered by Azure AI Document Intelligence and Azure OpenAI Service, is a groundbreaking solution that empowers you to unlock the full value of your documents and harness the capabilities of large-scale, generative AI models. This innovative solution offers a range of benefits, allowing you to:
By leveraging Document Generative AI, you can save precious time, reduce costs, enhance accuracy, and tap into your creativity when it comes to document workflows. Whether you require intelligent document chat capabilities, writing assistance, query support, comprehensive search functionality, or even document translation, Document Generative AI excels at handling complex and diverse document tasks through the utilization of state-of-the-art AI models from OpenAI.
Embrace the future of document processing and take your enterprise data to new heights with Document Generative AI, a cutting-edge solution that will revolutionize the way you work with documents.
In our previous blog post titled "Revolutionize your Enterprise Data with ChatGPT: Next-gen Apps w/ Azure OpenAI and Cognitive Search," we delved into the remarkable potential of Azure Cognitive Search for building powerful Chat Apps solutions. In this blog post we’ll describe how to extract information from your documents in order to enable chat on a variety of documents (scanned PDFs, digitized PDFs, images, office docs) with tables and long documents that exceed the limit size of an OpenAI prompt length. Our goal is to give you the tools necessary to build ChatGPT-powered applications starting today, using Azure OpenAI models and Azure AI services.
Chatting with documents has several challenges –
To address the challenges of chatting with diverse document types and long documents, leveraging Azure AI Document Intelligence, Azure Cognitive Search and Azure OpenAI models together can provide effective solutions. By combining Azure AI Document Intelligence OCR and Layout extraction capabilities, document parsing techniques, and using an intelligent chunking algorithm, you can overcome format variations, ensure accurate information extraction, and efficiently process long documents. This empowers you to create chat-based applications that can handle a wide range of document types and seamlessly interact with lengthy documents, extracting valuable insights and enabling meaningful conversations.
You can use Azure AI document intelligence to ingest your documents into Azure Cognitive Search with the following solutions and services:
python data_preparation.py --config config.json --njobs=4 --form-rec-resource <form-rec-resource-name> --form-rec-key <form-rec-key> --form-rec-use-layout
This github sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure Cognitive Search for data indexing and retrieval. You can Ingest your data into Cognitive Search using Azure AI Document Intelligence to extract information from documents PDFs and images see sample script here.
By using Document Generative AI, you can now chat with your documents. For example lets chat with invoices, contracts and SOWs using Azure OpenAI on your data service and ingesting the documents with Azure AI document intelligent layout service to preserve table information and document layout. In this scenario a Finance manager from Adventure Works is checking latest invoices. Amount of latest invoice from Contoso is pretty high ($6.5k). After checking line items, $5K for web hosting was found. Finds corresponding PO and SOW, checks that amount is matched but still wondering who signed such an expensive contract and finds out that it is company's CEO.
Example of a chat in the github sample app -
Example of a chat in the Azure OpenAI on your data Web App -
Example of a chat in the Azure OpenAI studio using Azure OpenAI on your data -
Note how now you can chat with tables, understand tables and line items and unlock the information hidden within your documents. You can also verify that the responses are trustworthy by viewing the citations. Each statement in the response includes a citation with a link to the source content. You can see the citations in context (the superscript numbers) as well as the links at the bottom. When you click on one, we display the original content so the user can inspect it.
In this blog post we focused on conversation and question answering scenarios on your documents that combine Azure AI Document Intelligence, ChatGPT from Azure OpenAI Service with Azure Cognitive Search as a knowledge base and retrieval system. There are many scenarios and use cases in which combining these services can improve your workflow and productivity:
You can get started and try this out now via the Azure OpenAI Service on your data capability or via the sample code in this GitHub repo. These solution both include the complete UX shown in this blog post, We plan on continuously expanding our service and this repo with a focus on covering more scenarios.
We’re excited about the prospect of improved and brand-new scenarios powered by the availability of large language models combined with Document Generative AI solution. We look forward to seeing what you will build with Azure OpenAI, Azure AI Document Intelligence and Azure Cognitive Search.
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